Tencent and Alibaba announce dividends after earnings, will SMIC and Hua Hong carry the baton next?
騰訊控股2026Q1業績直播（即時傳譯）
Key Takeaways (AI-Generated)
Financial Performance:
- Tencent reported Q1 2026 revenue of RMB 196 billion, up 9% year-on-year.
- Gross profit rose to RMB 111 billion, reflecting an 11% increase year-on-year.
- Operating profit showed a significant increase, reaching RMB 67.4 billion, up 17% year-on-year.
- Non-IFRS net profit attributable to equity holders was RMB 68 billion, up 11% year-on-year.
Business Progress:
- Tencent has made significant advancements in AI, launching Hunyuan 3 Preview, a robust large language model enhancing reasoning and agent capabilities.
- Notable growth in telecommunications and social networks, with Weixin and WeChat reaching 1.4 billion MAUs.
- Tencent Video solidified its leadership in animated content, while online game titles like Honor of Kings and Peacekeeper Elite achieved record revenue.
- Expanded data sets and capability enhancements in data collection, cleansing, synthesis, training and evaluation have been instrumental in propelling Tencent's AI initiatives.
Opportunities:
- AI-driven enhancements and the adoption of AI-based tools (like the Hunyuan model) across diverse applications provide a significant opportunity to boost productivity and user engagement across Tencent’s platforms.
- Growth in Tencent Cloud and FinTech services continue to drive significant revenue opportunities.
- Increased use of generative AI in content creation and marketing promises to maintain and enhance Tencent's competitive edge in producing animated series and games.
Next Quarter Guidance:
- Expected substantial increase in CapEx in the second half of 2026 due to increased demand for AI-related services and the availability of China-designed ASICs.
Risks:
- The pace of growth and revenue recognition from Tencent's AI services may face constraints due to operational scaling and integration challenges.
Full Transcript (AI-Generated)
Wendy Huang
Good day, and good evening. Thank you for standing by. Welcome to Tencent Holdings Limited 2026 First Quarter Results Announcement Webinar. I'm Wendy Huang from Tencent IR team. [Operator Instructions]. And please be advised that today's webinar is being recorded.
Before we start the presentation, we would like to remind you that it includes forward-looking statements, which are underlined by a number of risks and uncertainties and may not be realized in the future for various reasons. Information about general market conditions is coming from a variety of sources outside of Tencent.
This presentation also contains some unaudited non-IFRS financial measures that should be considered in addition to, but not as a substitute for measures of the group's financial performance prepared in accordance with IFRS. For a detailed discussion of risk factors and non-IFRS measures, please refer to our disclosure documents on the IR section of our website.
Now let me introduce the management team on the webinar tonight. Our Chairman and CEO, Pony Ma, will kick off with a short overview. President, Martin Lau; and Chief Strategy Officer, James Mitchell, will provide a business review; and Chief Financial Officer, John Lo, will conclude with financial discussion before we open the floor for questions. I will now pass it to Pony.
Huateng Ma
Thank you, Wendy. Good evening. Thank you, everyone, for joining us. We start 2026 by making significant initial progress on our new AI products so as continue to utilize AI to grow our existing core business. They review model built by our revamped team of AI researchers on the architected AI infrastructure is a leader in its parameter size class, delivering practical utilities and cost efficiency and has been top ranked in open router token measure since April 28. Our productive AI agent solutions have attained early adoption, and we believe that our work body is currently the most widely used productivity AI agent service in China.
Our core businesses continue to grow their engagement, revenue and profit, providing the cash flow to fund our AI investments as well as use cases for future AI deployments. Looking at our financial numbers for the first quarter. Total revenue was RMB 196 billion, up 9% year-on-year. Adjusting for the impact on revenue recognition for our value-added services from the later Spring Festival this year compared to last year, total revenue would have increased 11% year-on-year. Gross profit was RMB 111 billion, up 11% year-on-year. Non-IFRS operating profit was RMB 76 billion, up 9% year-on-year. Excluding new AI products, non-IFRS operating profit was RMB 84 billion, up 17% year-on-year and non-IFRS net profit attributable to equity holders was RMB 68 billion, up 11% year-on-year.
Turning to our key services. For communications and social networks, combined MAU of Weixin and WeChat grew year-on-year and quarter-on-quarter to 1.4 billion. For digital content, Tencent Video solidified its leadership in animated series with animated titles ranked top 10 industry-wide in the first quarter of 2026. For games, Honor of Kings and Peacekeeper Elite achieved record highs in gross received during the first quarter of 2026, while newly released creator collecting game, Roco Kingdom World achieved breakout success. Tencent Cloud's AI agent solutions achieved rapid growth and healthy retention rate.
Now I will hand over to Martin for the business review.
Chi Ping Lau
Thank you, Pony, and good evening, and good morning to everybody on the call. For the first quarter of 2026, our total revenue was up 9% year-on-year. As Pony mentioned, our total revenue growth was impacted by the later timing of Spring Festival this year compared to last year, which shifted to more games-related revenue recognition to future periods. Adjusting for the timing of the Spring Festival, total revenue would have been up 11% year-on-year on a like-for-like basis.
By segment, VAS represented 49% of our total revenue within which Social networks subsegment was 16%. Domestic Games subsegment was 23% and international games was 10%. Marketing Services was 19% of total revenue, and FinTech and Business Services was 31%. Our gross profit was up 11% year-on-year in the first quarter to RMB 111 million. VAS gross profit increased 9% year-on-year and represented 54% of our total gross profit. Marketing Services gross profit increased 19% year-on-year, contributing 19% of total gross profit. And FinTech and Business Services gross profit increased 13% year-on-year, contributing 28% of total gross profit.
Now a bit of update on our AI initiatives. Over the last 6 months, we have made significant progress on our Hunyuan large language model, but I would say it's just getting started. We started the initiative by completely overhauling our foundation model team, centering around newly added elite AI researchers and engineers with deep expertise in large language models. Our new team is young, energetic and cohesive, enabling us to make progress quickly in this highly dynamic AI era.
In February, we reengineered the system and process for pretraining and reinforced learning from the ground up. We rearchitected the infrastructure to support robustness, scalability and efficiency across pretraining, data and reinforcement learning. On data, we expanded our data set significantly and strengthened our data collection, cleansing and synthesis capabilities with a focus on data quality. On training, we upgraded the process for pretraining and supervised fine-tuning, and we scaled up reinforcement learning. And for evaluation, we're moving away from chasing public benchmarks that can be gained. Instead, we evaluate our model through the latest Sams, human tests, product feedback and in-house tasks to see how the model actually performs in the real world.
In April, we launched Hunyuan 3 Preview, when we set out to build this model, the purpose was to build a cost-efficient and solid model for diverse applications and derisk scaling toward larger models. The core design principles behind Hunyuan 3 Preview was to deliver comprehensive intelligence and cost efficiency, optimizing it for real-world deployment. We moved beyond narrow expertise and towards comprehensive intelligence such as integrating reasoning, long context understanding, instruction follow, dialogue, coding and 2-use capabilities. And by codesigning inference with model, we're able to reduce costs significantly so that the intelligence is economical enough to be used at scale.
Hunyuan 3 Preview has delivered on these expectations. The model has already become a leading reasoning model in China and has proven effective in real-world software engineering and other productivity agent tasks. Internally, the model has been deployed across 131 widely used internal products, including Yuanbao, QQ and WorkBuddy, providing valuable feedback and iterative improvement vehicle design process. And externally, Hunyuan 3 Preview has been well received by users and developers in real applications. It has ranked first among all models available on open router by token usage since April 28 and continued its lead even after its free period ended on May 8.
While significant strides have been made with Hunyuan 3 Preview, we view this as merely just the first step for Hunyuan large language models. The next step is to scale up to larger models. Our Hunyuan team is already working on a larger parameter model, leveraging our infrastructure and learnings from Hunyuan 3 by aggregating bigger and better data sets and scaling more powerful reinforcement learning, we can strengthen the model's contextual understanding, enhance its agent capabilities in areas, including coding and increase the model's general intelligence.
Through codesigning and collaborating with other Tencent product teams, we are optimizing data set selection and focusing reinforcement learning for high-value use cases. Beyond foundation models, it has become increasingly evident that agent AI represents a breakthrough use case after AI chatbots have become popular. Their agents are more valuable in uplifting productivity from initial use cases supporting programmers in creating code, such as with our product CodeBuddy to now catering to a wider range of workloads and occupations such as with Claws and WorkBuddy. These breakthroughs were made possible by more powerful models and by the hardness infrastructure that allows models to utilize tools and act as interfaces that enable users to manage agents effectively.
Our platform inherently has many benefits of hosting AI agents as users can control AI agents through our communications and browsing interfaces such as Weixin, WeCom, QQ -- Yuanbao and QQ Browser in addition to third-party applications. Users can also choose which model to use from a wide range of models based on their own needs and preferences on token cost and performance. And in the future, AI agents will be able to access our Mini Programs ecosystem using Mini Programs codes as AI skills.
Tencent has established an early lead in agent AI deployment evidenced by the leading DAU of our product, WorkBuddy. While early in adoption cycle, CodeBuddy and WorkBuddy are already achieving strong organic growth and high retention rates among active users and paying users. The high time spent and high-frequency interaction with AI agents among early adopters act as a virtuous feedback loop to Tencent, enable us to identify and provide complementary software and services, which in turn drives increased AI agent usage among a broader enterprise and prosumer user base. As users utilize more AI agents for more complex tasks, paying user conversion increases, resulting in rapid growth in token usage on Tencent Cloud in recent weeks.
Now with that, I will pass on to James.
James Mitchell
Thank you, Martin. Turning to business segments. Value-added services revenue was RMB 96 billion, up 4% year-on-year. Social network revenue was down 2% year-on-year to RMB 32 billion, reflecting decreased reported revenue from app-based game item sales in China arising from the late Spring Festival. Long-form video subscription revenue decreased 2% year-on-year due to fewer releases of top-tier drama series. However, we cemented our leadership in animated content with 8 of our self-commissioned series ranking among the top 10 across all video platforms in China during the quarter.
We believe Tencent Video possesses competitive advantages in creating animated series, including our ability to cross over IP from China literature and our games into animated IP and our use of technology tools such as Unreal Engine and generative AI for storyboarding and producing the animated content. Tencent Music subscription revenue increased 7% year-on-year, driven by growth in ARPU and subscribers.
For domestic games, gross receipts grew at a teens percentage rate year-on-year due primarily to Delta Force, Peacekeeper Elite, Honor of Kings and Valorant Mobile. However, revenue growth of 6% year-on-year lagged the gross -- receipt growth as later timing of the Spring Festival shifted some revenue recognition into the second half of 2026. International game revenue increased 13% year-on-year, mainly driven by Clash Royale, Wuthering Waves and Valorant.
Moving to Communications and Social Networks. Our Mini Shops transaction volume sustained a rapid growth rate. To better support merchants selling branded products, we introduced incentives, including preferential take rates for brands, product subsidies and prioritize recommendations. Branded merchants GMV more than tripled year-on-year in the first quarter, particularly in key categories such as FMCG and beauty. For consumers, frequent buyers can use our new coupon sharing feature to share discount coupons with friends via chats, benefiting from Weixin's virality. And for content creators, we upgraded the matchmaking mechanism so creators can more efficiently outreach to relevant merchants promote the merchant's products in the creators' video accounts and official accounts.
On the AI front, we have enabled Weixin and QQ to act as communication interfaces for controlling AI agents, allowing users to orchestrate agents from mobile for complicated task execution on PC and cloud. We scaled up the number of parameters and enhanced the algorithm for video accounts content recommendation model, enabling deeper understanding of users' interest to recommend more personalized and relevant content and total time spent on video accounts increased over 20% year-on-year.
For Mini Programs, we've upgraded the developer toolkit architecture so users can better leverage AI plug-ins, including CodeBuddy to create and debug Mini Programs. And over time, will enable Mini Program code to evolve into skills for AI agent used within Weixin. Total query volume on Weixin search increased over 25% year-on-year, benefiting from foundation model powered ranking and broadening AI search coverage to include image-based queries.
Moving to domestic games. During the first quarter, Honor of Kings achieved lifetime high quarterly gross receipts, benefiting from top-tier outfits inspired by Chinese things and Ancient Silk Road culture. For Peacekeeper Elite, peak DAU reached a lifetime high of 90 million and gross receipts increased over 30% year-on-year. The expanding user-generated content platform within the game, a new class-based extraction mode and IP collaborations with partners such as Ferrari contributed to the growth in users and gross receipts. Delta Force also achieved lifetime highs in average DAU and gross receipts for the quarter, benefiting from a Cosmic Guardian Skin, the Morphosis season featuring a revamped Space City map and crossover promotions.
Among newer games, Valorant Mobile has consistently ranked among top 10 mobile games industry-wide since its launch in August last year. And during the first quarter, we released distinctive weapon items such as Ignite Capsule, which contributed to strong gross receipts. Roco Kingdom World, a creature collecting open world game released on March 26. In its first month since launch, the game has achieved over 13 million average DAUs and is sustaining high user retention rates with its mobile version consistently ranked among the top 10 mobile games in China by gross receipts.
Taking a step back from these individual game titles, AI provides increasingly helpful tools, facilitating our game developers to deliver more content and enhanced experiences. Currently, AI for games is most beneficial in areas, including accelerating 3D asset production and animation, enriching player experiences with intelligent in-game guides and delivering more realistic graphics via AI rendering techniques. Among our international games, PUBG Mobile's gross receipts grew year-on-year in the first quarter, benefiting from Eastern mythology outfits, brand collaborations and anniversary events. For League of Legends, Riots conducted a substantial revamp of the team processes and technology in the last 2 to 3 years, which are now collectively resulting in a faster velocity of big new content releases, including the popular ARAM Mayhem constant team fight mode, a well-received new season in for Demacia and the Renant Reign Exaltede tier outfit for the Champion Viego.
As a result, League of Legends is experiencing a resurgence in DAU and gross receipts. Wuthering Waves new season For You Who Walk in Snow delivered a new map content and characters, contributing to the games gross receipts growth during the period. And after a consolidation period, Rothstar's DAU and gross receipts grew rapidly year-on-year, benefiting from new abilities for [ Bies ] and upgraded broadcast and an improved trophy system.
For Marketing Services, revenue grew 20% year-on-year to RMB 38 billion with notable growth from Internet services, e-commerce and gaming. Revenue growth improved from 17% year-on-year in the fourth quarter as we deepened collaboration with e-commerce platforms and as advertising demand picked up in response to increased inventory from video accounts. Our automated campaign management solution, AI Marketing Plus powered around 30% of total marketing services spending from advertisers with us in the quarter.
We upgraded our runtime advertising recommendation models with a unified transformer-based architecture. This upgrade provides deeper understanding of user context and the intent while balancing model complexity with system efficiency.
By inventory, video accounts ad impressions grew rapidly year-on-year, supported by increased total time spent video views and ad load. We released more inventory of rewarded ads, which deliver high click-throughs for advertisers. Mini Game and Mini Drama Studios increased their marketing spend within Mini Programs. Specifically for Mini Games, we've introduced an instant play advertising format, enabling users to play the game within the ad without needing a redirection, which reduces friction in the new user acquisition process. And through our mobile ad network, we've made more rewarded or incentivized ad formats available to third-party app developers, which unlocks higher price bidders and thus more revenue.
Looking at FinTech and Business Services, segment revenue was RMB 60 billion, up 9% year-on-year. FinTech services revenue growth is primarily driven by commercial payment volume by wealth management services. For commercial payment volume, year-on-year growth was faster than in the fourth quarter of last year, benefiting from an ongoing increase in the number of transactions, but also higher value per transaction in categories such as retail and dining services. For Wealth Management, average assets per user and number of users each increased year-on-year.
Turning to Business Services. Revenue in the first quarter grew 20% year-on-year, driven by increased demand and better pricing environment for our cloud services alongside rising technology service fees generated from mini shops e-commerce. For Tencent Cloud, AI-related demand contributed to increased revenue year-on-year across GPU, CPU and storage. We upgraded Tencent Cloud's AI agent solutions with proprietary security infrastructure, skill hubs and interfaces, contributing to rapidly increasing usage and initial token monetization.
Tencent Cloud's international business grew its revenue over 40% year-on-year as we expanded our global footprint and captured demand for our Platform-as-a-Service solutions, including media processing services and TDSQL cloud database. And now I'll pass to John.
Shek Hon Lo
Thank you, James. For quarter 1 2026, total revenue was RMB 196.5 billion, up 9% year-on-year. Gross profit was RMB 111.3 billion, up 11% year-on-year. Operating profit was RMB 67.4 billion, up 17% year-on-year. Interest income was RMB 4 billion, up 7% year-on-year, mainly driven by growth in cash reserves. Finance costs were RMB 3 billion compared with RMB 3.9 billion in the same quarter last year, primarily due to higher ForEx gains and lower average interest rate.
Share of profit of associates and joint venture was RMB 3.6 billion compared with RMB 4.6 billion in the same quarter last year. On a non-IFRS basis, share of profit was RMB 7.1 billion compared with RMB 7.6 billion in the same quarter last year. Income tax expense increased by 6% year-on-year to RMB 14.5 billion on non-IFRS financial figures. Operating profit was RMB 75.6 billion, up 9% year-on-year. Operating profit, excluding new AI products was RMB 84.4 billion, up 17% year-on-year. Net profit attributable to equity holders was RMB 67.9 billion, up 11% year-on-year. Diluted EPS was RMB 7.364, up 12% year-on-year, outpacing non-IFRS net profit growth due to reduced share count after our share buybacks.
Moving on to gross margins for Q1. Overall gross margin was 57%, up 1 percentage point year-on-year by segment. VAS gross margin was 63%, up 3 percentage points year-on-year, primarily driven by increased revenue contributions from internally developed games. Marketing services gross margin was 55%, down 0.5 percentage points year-on-year, reflecting higher cost of revenue, including AI-related equipment depreciation and associated operating costs as we increase AI investments to deliver more relevant content recommendations in the future.
FinTech and Business Services gross margin was 52%, up 2 percentage points year-on-year due to improved revenue mix within fintech services. On Q1 operating expenses, selling and marketing expenses were RMB 11.3 billion, up 44% year-on-year, reflecting increased promotional efforts to support the growth of our AI native applications and games, including new games. R&D expenses rose by 19% year-on-year to RMB 22.6 billion, primarily due to our increased investment in AI, which drove high equipment depreciation and associated operating costs as well as higher staff force.
G&A, excluding R&D expenses decreased by 24% year-on-year to RMB 11.3 billion, reflecting a high base in the prior year period, which included a of RMB 104 billion share-based compensation expense related to the restructuring of an existing commercial arrangement at an overseas subsidiary. At quarter end, we had approximately 113,000 employees, up 5% year-on-year, driven by headcount additions to gains in our technology platform, including AI-related headcount and down 1% Q-on-Q, mainly due to lower headcount at our independently operated subsidiaries and in-house tech support subsidiaries.
On Q1 non-IFRS operating margin was 38.5%, stable year-on-year. Non-IFRS operating margin, excluding new AI products was 43%, up 3.1 percentage points year-on-year.
To conclude, I will highlight some key cash flow and balance sheet metrics. Operating CapEx was RMB 31.2 billion, up 18% year-on-year and 84% quarter-on-quarter as we accelerated investment in server infrastructure. Nonoperating CapEx was RMB 0.7 billion. Free cash flow was RMB 56.7 billion, up 20% year-on-year, driven by growth in games, gross receipts and advertising billings, partly offset by higher server infrastructure and compute spending. On a Q-on-Q basis, free cash flow was up by 67%, reflecting seasonally higher game gross receipts and the timing of certain seasonal accounts payable settlements, partly offset by higher server infrastructure and compute spending.
Net cash position was RMB 146.9 billion, up 37% quarter-on-quarter or roughly RMB 40 billion, mainly driven by free cash flow generation, partly offset by share repurchase of RMB 7.9 billion and net cash outflows of RMB 7 billion related to investment in other corporations. Thank you.
Wendy Huang
Thank you, John. We shall now open the floor for questions. We will take the first question from Alicia Yap from Citigroup.
Alicis a Yap
Thanks for taking my questions. Two questions. First, since the release of Hunyuan 3 Preview, I think management also mentioned so the model has been deeply integrated to a lot of the internal core products, so including the Yuanbao, [indiscernible] and WorkBuddy. Then can management share some details on the performance enhancements that you have observed in these workflows since the adoption? So then additionally, what is the road map of integrating Hunyuan 3 more broadly into WeChat workflows? Will Mini Programs, enterprises will be able to leverage these agent workflows to improve their productivity and maybe future monetization?
Second question is with agents increasingly potentially replacing the traditional click-throughs on the web pages and also the apps, could management share your view on the future advertising pricing and also the resulting impact on advertiser budget? So what type of digital content or the web activities are likely to be -- remain more resilient, continuing to capture more significant user engagement? Are we thinking ahead and strategically maybe positioning our ad formats to adapt to this potential shift in the ad spending? So any thoughts or insight you could share would be helpful.
Chi Ping Lau
Thank you, Alicia. In terms of Hunyuan 3, we have given a pretty comprehensive overview of Hunyuan 3. And as you can see from the prepared remarks, it's more intelligent and it's actually very strong in terms of reasoning despite being a smaller model. And at the same time, it has significant improvement vis-a-vis Hunyuan 2 on agent capabilities. So with that, when we actually integrate Hunyuan 3 into the different products, the performance was actually quite, I would say, quite encouraging. The different products have all expressed and marked improvement in terms of the performance because they actually sort of see it from the user end. And the total token usage is actually at least 10x compared to Hunyuan 2, so that's the clear indication that Hunyuan 3 is actually well designed.
And at the same time, because it benefits from a co-designing process with some of the major products, for example, Yuanbao and WorkBuddy, right? So that's why it's well received by the products. In terms of the integration into the Weixin workflow, I think it will be a step-by-step process. And Weixin itself actually sort of have been always using some part of their products, Hunyuan 2 and they upgraded already to Henyuan 3. And in some cases, they use different models and they evaluate different models and evaluate what's the best model to use for their users, right?
So as Henyuan 3 continue to be getting better and better, then they will be adopting more. Now in terms of Mini Programs, I would say for the enterprises, one benefit is actually that they would be using some of our Hunyuan-enabled products such as coding or such as CodeBuddy as well as WorkBuddy, right? If these companies are actually using or the users are using such products, then they would actually be able to benefit from the improved performance of Hunyuan 3 and at the same time, in the future, when we start integrating Mini Programs as skills, right, to allow agents to have the ability to use Mini Programs as tools, then that would actually sort of add more traffic to these Mini Program enterprises. So one is internal, right?
When they use our own agent products, they can improve their own productivity. And the other one is external. It can actually help their Mini Programs to be used by more users and more agents going forward.
James Mitchell
Alicia, on your question on advertising, which is an interesting question. It's certainly more of an issue potentially for e-commerce companies than it is for us because users actively choose and desire to spend their time watching short videos or listening to music or consuming content or chatting with their friends versus generally speaking, when users spend time on e-commerce, it's because they're trying to find the lowest price. It's not because they necessarily enjoy that process.
So to the extent that AI agents play a bigger role in the future in facilitating price comparison, then it's possible that users will spend less time on e-commerce sites and be less exposed to ads than they are today, while the AI agents can scan infinite listings and therefore, not influenced by ads the way that human beings with a finite attention span are influenced. All of that said, there's been many prior iterations of price comparison services, including search engines and the big e-commerce companies are generally thrived despite the existence of those price comparison services. So I think it's premature for us to sort of have a definitive view at this point on how it will affect our friends in the e-commerce industry. But we don't see it as a primary risk for Tencent. Thank you.
Wendy Huang
We will take the next question from Kenneth Fong from UBS.
Kenneth Fong
I have a question on the ROI on AI investment. If we look at the global peers, they have been allocating 80% to even 100% of their operating cash flow to AI CapEx compared to us, which we invest roughly 35% in the last quarter. But however, many of them have experienced decline in free cash flow, ROE as the business become more asset heavy. So could management share or provide more quantifiable guidance on the AI-related CapEx for this year? And what KPIs are being used to assess the value creation and return on this investment?
Huateng Ma
Kenneth, so we are seeing increased demand, both from internal products as well as from external users of our model for our AI-related services. And we had previously guided that we'll be increasing CapEx this year versus last year, and we're now more affirmative, more confident in that guidance. And we and you should expect a substantial increase in CapEx, especially in the second half of this year as more China designed ASICs become available to us month by month through the year. On the KPIs, they differ product by product and business by business.
At a high level, for our existing activities such as advertising and games, the KPIs would be more revenue and profit related. For our new AI products, the KPIs would be more capabilities, how intelligent is our foundation model and usage, how much token consumption is happening on WorkBuddy related. And then for Tencent Cloud, where until now, we actually haven't had sufficient GPUs to begin to service the external demand, the KPIs will be more revenue and market share related.
Wendy Huang
We will take the next question from Alex Yao from JPMorgan.
Alex Yao
I'd like to follow up with Kenneth's question just from a slightly different perspective. When you allocate financial resource to CapEx and AI investment, how do you evaluate the AI infrastructure spend internally? What is the ROI framework or payback period that you are underwriting these investments against and over what time horizon?
Shek Hon Lo
I think we provided some thoughts on how we view the sort of quantitative or qualitative return on investments in the previous answer. And there are certain products where we're taking a very sticky financial approach and others where we're more focused on the benefits to our franchise over time. I don't know if you want to sort of iterate on the questions. I may not have caught the full meaning behind the question.
Alex Yao
Thank you, James. I mean, ultimately, the investment community needs to understand who pays the AI CapEx from what budget and over what time period or horizon do we expect to tap into those new commercial opportunities.
James Mitchell
I think that in the history of Tencent, we have generally sustained good returns, and you can quantify that by looking at our return on equity over the last couple of decades, which has been a consistently high return on equity. But we have not got there by limiting each new product, each new service to very near-term quantitative return on investment targets. We have got there by managing the portfolio as a portfolio and by managing products over their full life cycle, not over any specific quarter or 12-month period.
And so there's been many products within Tencent, whether it's our expansion into games, the launch of Weixin, movement into payments that went through lengthy incubation periods where they had no return on investment, but we were confident in the franchise value creation. And then over time, they had more lengthy harvesting periods where we've been able to drive very healthy returns on that sunk investment. And AI includes a range of sort of shorter cycle investments as well as longer cycle investments.
And so if we buy GPUs and we deploy them into our ad tech, then that's a relatively short-cycle investment. The GPUs yield better targeting, higher click-through rates and higher revenue and profit on a pretty accelerated basis. On the other hand, when we deploy GPUs into our Hunyuan foundation model, that's something which we view as important for our franchise and where we're taking a longer-term view. But again, we don't manage each product on a quarterly basis. We manage the portfolio and we manage the products on a full life cycle basis.
Chi Ping Lau
I think just to elaborate on what James is saying, right, there's sort of a range of different ways to look at this, right? And if you look at the model training, it's basically an investment for the future, right? And there's probably not going to be very immediate return. But over time, the capability accumulates and it actually helps unlock a lot of different businesses opportunities. And then when you look at the products that we are launching, right, be it Yuanbao, WorkBuddy, CodeBuddy, right, there's process in which you have free services, right? And then over time, you may have revenue -- the business-oriented revenue can come faster than the consumer-oriented revenues.
So there will be sort of a return cycle on that. And then if you look at the business revenue sort of be it -- or the cloud revenue in the sense of [ PaaS ] or rental of compute, then there's a clear ROI, right? You have a depreciation cost and you usually put on some kind of margin and then sort of you rent out. So that would be sort of having a clearer return. And then when we have advertising, as James pointed out, right, we usually see very good return from those investments. So I think for different computes, there's different ways to look at it.
Wendy Huang
We will take the next question from William Packer from BNP Paribas.
William Packer
Firstly, with domestic gaming your biggest revenue and free cash flow driver, could you help us think through how generative AI is impacting that business today? Is it driving incremental monetization by faster content creation cycles? Or is that a delayed benefit? And are you seeing cost efficiencies benefit the margins today? Or do you need to invest the initial phase limiting any benefit? And I have a quick follow-up. Thanks for the commentary on the CapEx outlook. Could you talk through any implications for the share buyback in the second half of the year?
James Mitchell
Yes. So why don't I address those? As you hypothesize for our game business, generative AI enables us to produce more content faster. And that content is, in some cases, to enhance the overall player experience. But in some cases, it results in direct monetization. For example, if the content is a virtual outfit. And so that's what we are doing, and that's what we are seeing. And we think that we're a China leader and to some extent, even more so a global leader in terms of deploying that capability and achieving that benefit. And the objective at this point is really faster content creation and incremental revenue generation.
We're not prioritizing margin expansion per se. It's more that as we deliver the revenue uplift that we're seeing and if we can keep headcount fairly stable, then I suppose mathematically, that combination would tend to result in higher margins over time, but that's sort of a happy output rather than the intention of the process. And then in terms of your question about capital returns, we will be stepping up our investments in AI in response to the increased demand that we're seeing.
However, we do have a very cash-generative business, as you can see from the first quarter results. We also have a very substantial investment portfolio, and we're accelerating the process of liquidizing some of that investment portfolio and that will enable us to sustain buybacks going through the rest of this year. And at this point in time, we believe our share price is somewhat dislocated. And therefore, it's an opportune time for buybacks, a particularly opportune time for buybacks.
Wendy Huang
Next question comes from Robin Zhu from Bernstein.
Robin Zhu
If I could -- I have a couple of questions, so one, in terms of the changes that we've made to our data pipeline and training RL and so on. Do you feel now that having seen the release of Hunyuan 3, we're now on a more sustainable upward trajectory where we can deliver major updates, one major update a year, several smaller ones in between like some of the other labs. Are we there? Or is that still more of a work in progress?
And then second, just on the kind of philosophy of some of the AI product investments. I think one of the tensions in the U.S. has been -- I think OpenAI has been the big DAU player, whereas Anthropic has kind of gone after a small pool of high-intent power users, highly willing payers effectively. Just curious on -- I mean, Tencent obviously has historically been the former, but just curious your thoughts on kind of the relative merits of going down one path versus the other. And to what extent does the current kind of tokenizing phenomenon play into that pool?
Chi Ping Lau
In terms of the production pipeline, I think we have gone in pretty at length to talk about sort of how we felt it's actually making very good progress. If you look at Hunyuan 3, we have revamped the entire team, the production process, the infra and all the different major modules in producing great models, right, including the data pipeline, as you point out, the pretraining, the post-training, the RL as well as the eval. So -- and we have deliberately actually built a smaller model to basically validate all these different points, right? And the combination of this, right, when it's all integrated into Hunyuan 3 Preview is that it produces a pretty competent model at its size.
And we clearly see in each one of these modules, there's a lot of work that we could be doing. So I think we're happy with the results. To some extent, we are actually surprised by the speed at which it's done and the fact that it's actually proved to be useful, right? For a long time, I think a lot of models would actually come up pretty high in terms of the benchmarks. But then when it's actually rolled out to different products, people complain. And when you put the model to the developers and the user, right, people will use it, right?
So I think if you look at how this is received in the actual use cases, it's actually better than our expectation by quite a bit. And so with that, I think it builds a very solid foundation for us to scale the product -- the model to the next level. In terms of how we think about the different products, we felt this is actually sort of a very early stage in terms of AI diffusion, right? And we would see many different products coming up going forward. Initially, it was chatbot and everybody felt chatbot is actually the king of the product. And then suddenly, you have a coding that came up and this becomes sort of even more eye-catching and less significant use case because it's very high value, right? And now we are seeing sort of Agentic capability proliferating right?
And I think that would actually allow AI to be diffused to different industries, and you have many different agents coming up, which can help you to do work, right? And there's going to be new products coming up. So I think that would continue to propagate. And I think to some extent, right, you actually have to -- in the AI world, you actually have to find a high-value use case as opposed to sort of just purely focused on DAU because the difference between the AI revolution and Internet is that this is about intelligence and intelligence manifest its value in sort of how much people are willing to pay for it.
And at the same time, the intelligence is not free, right? In the Internet world, you basically sort of have mostly existing information. And then you also create some new information and content, but then that's a fixed cost and then sort of the variable cost for delivering is actually very small, right? You only have to pay for bandwidth and the compute sits on people's devices, right? And as a result, you can almost like go for infinite scaling. But in this case, right, every single delivery of a DAU actually cost you quite a bit.
And as a result, you can't just apply the same logic as Internet and apply it to AI. And I would say the ability to find high-value use cases is going to be as important, if not more important than just sort of blindly get a lot of use -- DAU and user time. So I think that is one important distinction. And as we think about it how to deploy our product and how to codesign our product with the models. So these are the kind of new considerations that we have to put into play.
Wendy Huang
We will move to the next one, Alex Liu from Bank of America.
Alex Liu
So I have 2 questions. So I appreciate the sharing on the Agentic AI strategy. I'm especially interested in the context that Tencent's AI agents could access the Mini Program ecosystem and use Mini Program code as AI skills. Just wondering on that, is there any time line we should expect for this to materialize? A follow-up would be related to the last question. Given the tight supply of computing resources right now, I was wondering how is management balancing the pace of rolling out additional AI features such as leasing agent against the current pretty tight compute capacity on hand.
Chi Ping Lau
Well, on Mini Program, I think this is something that will be coming. I think we need to figure out sort of what's the best way of presenting these and how to allow Mini Program owners to actually sort of actively engage this. So there's -- we have a timeline. We're not going to be able to share with you with a definitive answer because there's a lot of design that needs to come into place, right? But at some point in time, I think it's a concept that our ecosystem can actually help each other out, and this is one unique advantage that we have.
And over time, a lot of potential ecosystem resources can be actually turned into skills for agents. And over time, agents would actually sort of have their own identity and be able to get accounts in some of the services, too, right? So I think that's a unique advantage that we have and we'll be providing that over time.
James Mitchell
And on your question about balancing between the various AI products we would like to develop internally. The reality is we've already made the choice and paid the price in that we have prioritized a multiplicity of internal services ahead of Tencent Cloud. And so I think most big tech hyperscale companies with cloud businesses have one flagship internal use case where they're allocating a large number of GPUs. We have multiple flagships. We have the Hunyuan foundation model. We have agentic developments within Weixin. We have Yuanbao support.
We have the AI deployment for advertising for games, now also for the WorkBuddy and CodeBuddy use cases. And the reason why we have been able to support all of these at once is because we have not been active in leasing out GPU capacity in Tencent Cloud. Now looking through the rest of this year, as the supply of China design GPUs progressively ramps up, then we'll be remedying that situation, and we will be making more capacity available in Tencent Cloud and consequently driving up Tencent Cloud's rate of expansion. But that's where the trade-off has been made that we have been consciously late to monetize the AI opportunity through Tencent Cloud because we've been simultaneously supporting a number of AI initiatives internally.
Wendy Huang
We will take the next question from Charlene Liu from HSBC.
Charlene Liu
I have 2 questions. First is on monetization. We're seeing Doubao starting to explore subscription models for their 2C users. I would like to understand how big the management thinks that the 2C subscription market looks like in China? And I guess, subscription aside, are -- as and Mini Programs are shop key monetization avenue for 2C AI or there are more? And how much upside do you expect from Ads and Mini Programs? That's the first question.
The second question is on compute power bottleneck. The U.S. players obviously have sort of moved on to working on resolving bottleneck issues or shortages in CPU and networking chips beyond GPU. And has these issues begin to service? Do we anticipate it to? And what are the management's plans to resolve them?
Chi Ping Lau
In terms of the 2C monetization, I would say it's actually not easy, right? If you look at global standard in the Western market when the paid service is actually very well penetrated and the living standard is actually very high. So the subscription price in the Western market is multiple times of what the equivalent service in China is like, be it music service or be it video service. The paying penetration is probably in the single digit, right? And when you sort of applied it to China, I think the subscription model is not going to be that big for the China market.
You use that as a standard and then sort of start to read across for China, then it will not be that much. And at the same time, it's necessary, right, for the reason that I talked about, it's not like Internet services in which you can have very low cost of scaling your services, right? Every single user actually sort of cost you something in terms of variable cost. And I think the more important implication is that when you have to have payment to support a service, then most likely the service is not going to be a winner take-all business.
It would basically sort of be supporting multiple players who would have a share of the market and each one of them would sort of have some kind of users and some share of subscriptions. And beyond that, right, when we look at e-commerce or advertising as a way to monetize, I think it's also very early for even the U.S. players where the eCPM is actually much higher, right? The leading player has not been able to roll out very robust advertising model. And so I think it will be for the longer term, and it will be supplement to probably a subscription model.
So I think that's why I said in the world of AI, when you apply the compute and apply the model to different use cases and different applications, you actually need to think about what is actually the high-value use case so that you have the best return on your limited compute in order to achieve the best results.
Shek Hon Lo
And in terms of your question about the various bottlenecks between GPU, CPU, networking and so forth. To recap that the reason why there's been a GPU bottleneck that's been much more pronounced in China than elsewhere is a combination of policy restrictions on certain foreign design GPUs being brought into China and then the China design GPUs facing limited fab capacity within China. And as a result, the country has really been short of GPU or ASIC capacity. And that's now being addressed because the China designed ASICs are seeing more supply from fabs within China as well as more supply from fabs in neighboring countries.
But by contrast, we haven't faced those sort of artificial additional constraints, CPU or networking chips. We've been a big buyer of CPU and networking chips for many years before GPUs became such a big presence in data centers. We have very long-term relationships with the companies that supply the CPUs and supply the networking chips.
And on their side, while one might think that these suppliers would be sitting back and just selling at the highest possible price into the spot market, that's not actually the reality. The smart suppliers are taking very conscious 3- to 5-year forward views and negotiating long-term agreements in order to give them certainty of their revenue outlook over the next 3 to 5 years. And when they're deciding with whom to sign those long-term agreements, they're looking to work with a number of partners, not just a single partner, and they're looking to work with partners who have been there for many years already and will be there for many years to come and ideally with partners whose demand they believe will grow substantially over time.
And happily, we fulfill all of those criteria. We've been a big customer for the Intel and AMD and so forth for many years. We've been progressively growing our volume with them for many years, and they believe it will continue to progressively grow our volume for many years to come. So on the procurement side, I'd say that the challenges are more around GPU and those challenges are now being addressed. And then we've been able to secure a good supply of CPU and networking chips.
Wendy Huang
We will take the next question from Ronald Keung from Goldman Sachs.
Ronald Keung
So 2 questions. One is on the consumer AI agent side. So compared with a potential kind of Weixin agent that we've been talking about, which is at the app level, knowing that Weixin is a super app, but how does management view long-term potentials or potential disruptions from operating system-level agents, noting agents from iOS or Android or mobile phone by phone makers. So how would we see that potential or disruption or threat?
And then second, on advertising, we've seen a very good reacceleration. Noting that we are very patient on ad load versus peers, but with a slight kind of hedge up of ad load in the first quarter, I'm just thinking, is there any room for any thinking or change to have a potential further revenue acceleration for ads and reason, I would say, thinking bigger advertising profits could drive more reinvestment into AI. So would love to hear your thoughts.
Chi Ping Lau
I think from an operating system perspective, right, you mix in a number of different things, right? There is a real operating system, which is iOS and Android, right? And there are -- and then you log in sort of your other applications, which try to pretend to be operating systems. So I think if you are operating system like iOS or Android, then you actually want to make sure that the ecosystem is actually well protected and well curated and given whatever that you actually allow applications to do, right, you actually want to have that balance, right?
You can have an agent which try to provide services to your users, but then you actually need to have the permission, right, of the different applications. Otherwise, as an operating system, you are essentially dropping different apps. And that's not the best way of managing an operating system. So I think operating system has existed for a long time and the principle of an operating system is actually -- it's very neutral, and it actually provides a level playing field for all the apps. And in the future, all the agents to be working with the operating system.
But if you say, there's another app which sort of try to become an operating system like a service and try to sort of invade other apps, I think that's a real competition, and that's not something which any app would actually allow. And I think the operating system itself, which should try to sort of stop that from happening as well. So I think if you're talking about agents, which will sort of be an app trying to compete with other app, I think that's one level of right? And I think operating the system will always try to be quite impartial and try to maintain a healthy ecosystem for everybody to be involved in order for it to be a successful ecosystem or operating system.
James Mitchell
And in terms of the advertising revenue, actually, our ad load on video accounts is still the lowest in the industry at 4% to 5%. So there's clearly a substantial headroom for us to increase the ad load. As to whether -- and to what extent we'll sort of feel the need to do so, we are in a position where we have multiple revenue growth drivers beyond advertising. For our game business, the jump in deferred revenue in the quarter provides us with a sort of tailwind to the reported revenue growth over the coming 3 quarters.
For our cloud business, we've talked about how bringing on stream more GPUs in the second half of the year should facilitate revenue growth trends for cloud. For our fintech business, for many quarters, we've been struggling with a situation where volume growth was positive, but pricing was negative. And now volume growth remains positive and pricing move to a more neutral start. So we feel that across our portfolio of businesses, there are certain positive things playing out. And we'll continue to manage it as a broad portfolio, and we'll continue to manage the ad load within video accounts in a way that we think is conducive to both supporting the overall growth of our business metrics, but also to supporting growth of time spent and engagement within the video accounts product itself.
Wendy Huang
We will take the next question from Ellie Jiang from Macquarie.
Ellie Jiang
I have 2 questions. Number one is, if you look at the WorkBuddy current traction, it does seem like we have been gaining very early leadership, especially in the productivity agent space. So within the 20% growth in business services this quarter, could you shed some light on what percentage of this would be kind of reoccurring Agentic revenue, i.e., be kind of MaaS or SaaS related versus the traditional cloud revenue as well as the others? And specifically, do you have any internal ARR target for these Agentic workflow products by the end of fiscal year '26 and in the next kind of 2, 3 years?
James Mitchell
Yes. The upturn in sort of productivity AI is really something that's happened not in the last few quarters or even last few months, but last few weeks. And I think that's true globally actually, that really -- it's since late in or since the end of the first quarter that the Agentic AI has broken through in terms of its ability to create code, in terms of its ability to make people more productive. And so in the first quarter, the business services growth was not a function of that token consumption. The token consumption has been more recent than the end of the first quarter. In terms of ARR targets and so on, by extension, this is all changing so quickly. That we could set a target today, and we'd be out by an order of magnitude 12 months from now in either direction because the usage demand is so dynamic.
So at this point, we're less focused on hitting certain dollar ARR numbers and more focused on having the right products and the right products includes the right product at the model level where Hunyuan 3 is very good in terms of many agentic capabilities. And the next iteration will be substantially better later this year and also at the product level in terms of CodeBuddy and increasingly WorkBuddy being the right interface for users to access and extract the most intelligence from these foundation models. So right now, that's a priority.
Wendy Huang
We will take the last question from Thomas Chong from Jefferies.
Thomas Chong
My question is about AI on the content side. Given that we have seen some disruptions coming from AI in the online video space, should we expect Tencent Video? We also have expecting AI drama to be a blockbuster content in the coming years? And how should we think about all the content cost and the business model going forward? And my second question is AI on the fintech segment. Given the risk management is substantially enhanced with AI, how should we think about the online lending and wealth management outlook with AI?
James Mitchell
But again, the landscape for AI has been so dynamic. Our own position has changed so much in the last few weeks, in the last few months that it's difficult to speak very definitively. I think when you talk about AI disruption in content creation, you may be alluding to mini videos or mini drama series rather than the long-form drama series that is historically Tencent video strength.
On the long-form side, then what we're seeing is that there is a certain double-digit percentage of the market that likes animated content. And now as a result of the confluence of tools such as Unreal Engine and capabilities such as generative AI for video, it's becoming increasingly feasible to create the same 3D assets for games and for animated content, animated linear video content and both become a very good best-in-class products within that particular categories. And so that's something where Tencent is a natural leader because we have our big content IP operations.
We have our game business. We have our AI technology capabilities. We have particular strength in certain multimodalities within AI. And so as Pony mentioned in the opening remarks, we've actually become a very clear industry leader now in the business of producing animated TV series and AI enables us to do that faster, cheaper, better. It also enables us to bring far more IP into linear video format that was previously sort of stuck in novel format or in game format. And so expand the funnel, expand the audience. So that's on AI for content.
And then on AI for fintech Financial services represents a very big part of global GDP. It represents a very big part of our revenue. It's an industry that is inherently very data heavy. And so it's naturally an industry that should and will lend itself over time to uplift in productivity from AI. And if you think about the industries that are already being uplifted by AI, such as coding, such as advertising, then financial services is actually very logical to be uplifted in the near future, too, because it shares certain characteristics with coding with advertising and so forth.
And so to give one example, on the lending side, then credit scoring has historically been more of an art than a science, and there's been this universe of data available, but only a small subset of that universe is actually fed into the model effectively versus now with transformer-based models, you can sort of take the totality of data available and see what is predictive and improve your loan extension on the basis of that uplift in predictability. So I think it's an area that many companies will be investing a great deal of time and energy and where we'll be participating as well.
Wendy Huang
Thank you. We are now ending the webinar. Thank you all for joining our results call today. If you wish to check out our press release and other financial information, please visit the IR section of our company website at . The replay of this webinar will also be available soon. Thank you, and see you next quarter.
Details at Tencent IR
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